mixAR_BIC | R Documentation |
BIC calculations for mixture autoregressive models.
mixAR_BIC(y, model, fix = NULL, comp_loglik = TRUE, index) BIC_comp(x, y)
y |
a time series. |
model |
the model for which to calculate BIC, an object inheriting from
class |
fix |
If |
comp_loglik |
Should the loglikelihood be calculated? Default is
|
index |
Discard the first |
x |
a list containing a combination of |
mixAR_BIC
calculates the BIC criterion of a given MixAR
object with respect to a specified time series.
If index
is specified, it has to be at least equal to the
largest autoregressive order. The function calculates BIC on the last
(index + 1):n
data points.
BIC_comp
calculates the value of BIC for the models listed in
x
with respect to the specified time series y
.
If the distributions of the components contain estimated parameters, then their number is included in the number of parameters for the calculation of BIC.
If comp_loglik = TRUE
, the function calculates BIC based on the
given model, data and index
.
If comp_loglik = FALSE
and model is output from
fit_mixAR
, it returns object vallogf
from that list.
Davide Ravagli
model1 <- new("MixARGaussian", prob = c(0.5, 0.5), scale = c(1, 2), arcoef = list(-0.5, 1.1)) model2 <- new("MixARGaussian", prob = c(0.5, 0.3, 0.2), scale = c(1, 3, 8), arcoef = list(c(-0.5, 0.5), 1, 0.4)) set.seed(123) y <- mixAR_sim(model1, 400, c(0, 0, 0), nskip = 100) mixAR_BIC(y, model1) model_fit1 <- fit_mixAR(y, model1) model_fit2 <- fit_mixAR(y, model2, crit = 1e-4) mixAR_BIC(y, model_fit1) mixAR_BIC(y, model_fit2) BIC_comp(list(model1, model2, model_fit1, model_fit2), y) mixAR_BIC(y, model_fit1, index = 20) mixAR_BIC(y, model_fit2, index = 20)
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